Nonlinear echo suppression

ABSTRACT

Presented is a method and associated system for suppression of linear and nonlinear echo. The method includes dividing an input signal into several frequency bands in each of a several of time frames. The input signal may include an echo signal. The method further includes multiplying the input signal in each of the several frequency bands by a corresponding echo suppression signal. Calculating the corresponding echo suppression signal may include estimating a power of the echo signal in a particular frequency band as a sum of several component echo powers, each of the several component echo powers due to an excitation from a far-end signal in a corresponding one of the several frequency bands. Calculating the corresponding echo suppression signal may further include subtracting the power of the echo signal in the particular frequency band from a power of the input signal in the particular frequency band.

RELATED APPLICATIONS

This application claims priority of U.S. Provisional Application No.61/516,088 filed on Mar. 28, 2011, which is hereby incorporated byreference in its entirety.

BACKGROUND

Echo cancellation is a requirement in many applications such asspeakerphones, entertainment theater systems, and audio digital signalprocessing. However, current echo cancellation methods either cancelonly linear echo, or are very computation-intensive in order to provideacceptable nonlinear echo modeling accuracy. For example, most echocancellation systems in the frequency domain comprise two components:linear adaptive echo cancellation (LAEC) and nonlinear suppression ofresidual echo (NLP). Current methods of nonlinear echo suppressionattempt to remove residual echo after LAEC application, utilizing echoreturn loss (ERL) and/or echo return loss enhancement (ERLE). Where ERLor ERL and ERLE are above a certain threshold NLP attempts to remove theresidual echo and insert comfort noise. Such methods may be useful wherethe linear echo canceller adequately removes linear echo and nonlinearecho is small. However, such methods may unacceptably clip or distortsoft voices spoken by local speakers.

In addition, current nonlinear echo cancellation techniques based onVolterra filters, for example, require many taps to achieve accuratemodeling of the nonlinear echo. Consequently, accepted adaptivefiltering algorithms for echo cancellation have high computation costsand tend to converge very slowly. Moreover, current nonlinear echocancellation techniques are based on the correlation between echo andresidual echo or between far-end and near-end signals in the samefrequency band. As a result, current echo suppression techniquesessentially suppress the linear echo component in a particular frequencyband. Accordingly, such techniques may be used to suppress nonlinearecho via overestimation of the linear echo only if the nonlinear echo isvery small. However, in general, these current methods cannot accuratelysuppress the nonlinear echo.

SUMMARY OF THE INVENTION

The present disclosure is directed to nonlinear echo suppression,substantially as shown in and/or described in connection with at leastone of the figures, and as set forth more completely in the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A presents an exemplary system for echo suppression, according toone implementation of the present application;

FIG. 1B presents an exemplary diagram of a processor within a system forecho suppression, according to one implementation of the presentapplication;

FIGS. 2A-2F present exemplary diagrams of several related signalspresent within a system for echo suppression, according to oneimplementation of the present application;

FIG. 3A presents an exemplary flowchart illustrating a method for echosuppression, according to one implementation of the present application.

FIG. 3B presents an exemplary flowchart illustrating a method forestimating a corresponding echo suppression signal, according to oneimplementation of the present application.

FIG. 3C presents an exemplary flowchart illustrating one or more methodsfor estimating each of a plurality of component echo powers, accordingto one implementation of the present application.

DETAILED DESCRIPTION

The following description contains specific information pertaining toimplementations in the present disclosure. One skilled in the art willrecognize that the present disclosure may be implemented in a mannerdifferent from that specifically discussed herein. The drawings in thepresent application and their accompanying detailed description aredirected to merely exemplary implementations. Unless noted otherwise,like or corresponding elements among the figures may be indicated bylike or corresponding reference numerals. Moreover, the drawings andillustrations in the present application are generally not to scale, andare not intended to correspond to actual relative dimensions.

FIG. 1A presents an exemplary system for echo cancellation, according toone implementation of the present application. As shown in FIG. 1 A,system 100 may include far end 110 and near end 120. Far end 110 mayinclude microphone 116 for detecting far end signal 102, which may bespeech or any other audio that is to be transferred from far end 110 toa listener at near end 120, for example. Far end 110 may also includespeaker 112 for broadcasting an echo-suppressed signal from near end120, for example. Far end 110 may also include processor 114, which maybe similar to processor 124 of near end 120, and may be configured toperform any number of processing actions as required by one or moreimplementations of the present application.

Far end signal 102 may be routed from far end 110 to near end 120 by anyappropriate means and input to processor 124, for example. Near end 120may further include speaker 122 for broadcasting far end signal 102 atnear end 120. Near end 120 may also include microphone 126 for receivinginput signal 108. Input signal 108 may include a desired signal 136 aswell as an echo signal. Such an echo signal may include direct-coupledsignal 132 and reflected signal 134, for example. Direct-coupled signal132 may result from microphone 126 picking up far end signal 102broadcasted directly from loudspeaker 122. Depending on thecharacteristics of environment 140 of near end 120, reflected signal 134may include linear as well as nonlinear echo of far end signal 102. Forthe purpose of the present application, echo is considered nonlinear ifthe echo produced by a particular signal contains harmonics of theparticular signal in addition to echo at the frequency of the particularsignal.

FIG. 1B presents an exemplary diagram of processor 124 within system 100for echo suppression, according to one implementation of the presentapplication. FIG. 1B presents processor 124 as in FIG. 1A, includingnonlinear echo canceller 154, which may be configured to performnonlinear echo cancellation according to one or more implementations ofthe present application. Processor 124 may also optionally includelinear echo canceller 152 connected to nonlinear echo canceller 154. Inimplementations including linear echo canceller 152, input signal 108and far end signal 102 may be received by linear echo canceller 152.Linear echo canceller 152 may be configured to generate a synthesizedecho 105, which may be an estimation of the linear echo at near end 120of FIG. 1A, based on input signal 108 and far end signal 102. Thus, inimplementations including linear echo canceller 152 residual signal 106may be equivalent to input signal 108 minus synthesized echo 105. Aswill be discussed in further detail below, one implementation mayinclude nonlinear echo canceller 154 utilizing synthesized echo 105 andfar end signal 102 to suppress nonlinear echo. Where linear echocanceller is not utilized, input signal 108 may be input directly tononlinear echo canceller 154.

Looking back to FIG. 1A, assuming that far end signal 102 output fromspeaker 122 is a tonal signal, we can expect to see harmonics of thetonal signal in the input signal from microphone 126. Mathematically,the nonlinear operation to such a tonal signal results in a linearcombination of the tone and its harmonics. Thus, if a single frequencyis played from speaker 122, the input signal from microphone 126 mayinclude signals in all other frequency bands. The stronger thenonlinearity of the environment at near end 120, the stronger will bethe harmonics of the tonal signal. However, because typical loudspeakersonly exhibit a small number of stronger harmonics, taking into accountonly the stronger harmonics may save considerable computational cost ina nonlinear echo suppressor.

Looking at nonlinear echo behavior from another viewpoint, input signal108 from microphone 126 in a particular frequency band includes delayedand distorted far end signal 102 in the same frequency band due tolinear coupling signal 132 as well as reflected signal 134. As statedabove, input signal 108 will also contain harmonics of the particularfrequency due to nonlinear echo in coupling signal 132 and in reflectedsignal 134, caused by near end environment 140. Thus, echo in aparticular frequency band has a number of components corresponding tothe number of frequency bands in far end signal 102, for example.Accordingly, echo in a particular frequency band may consist of Mcomponents, where M is the number of frequency bands. Because each ofthe M components is nonlinear echo, each component is uncorrelated toeach of the other components.

Let M, an integer, be the number of frequency bands used infrequency-band decomposition for nonlinear echo suppression. x(n,m) maydenote far end signal 102 at band m and during time frame n, which maybe broadcast out of near end speaker 122. y(n,m) may denote the echosignal due to direct-coupled signal 132 and reflected signal 134. d(n,m)may denote desired near end signal 136, which may include backgroundnoise and other local sounds that are not echo. Thus, input signal 108,z(n,m), received by microphone 126 may be denoted by:z(n,m)=y(n,m)+d(n,m) where 0 ≦m<M and n is the frame index

As stated above, the total echo in each frequency band m includes M echocomponents, specifically, one component due to the excitation caused byfar end signal 102 in each of the M frequency bands. Thus, the sum ofeach of these components is the total echo, y(n,m). Mathematically, thisrelation may be denoted as:

${y( {n,m} )} = {\sum\limits_{u = 0}^{M - 1}{y_{m}( {n,u} )}}$where y(n,m) is the total echo in frequency band m, and y_(m)(n,u) is acomponent of the echo in frequency band m, due to the excitation causedby far end signal 102 in frequency band u.

Nonlinear echo suppression according to the present application may beaccomplished utilizing a spectrum subtraction technique according to:{circumflex over (d)}(n,m)=g(n,m)z(n,m)where {circumflex over (d)}(n,m) is an echo suppressed output signal 104to be broadcast from speaker 112, for example, g(n,m) is a weightingcoefficient, and z(n,m) is the input signal 108, for example.

According to a first implementation, weighting coefficient g(n,m), for afrequency band m during timeframe n, may be computed according to:

${g( {n,m} )} = \lbrack \frac{{E\{ {{z( {n,m} )}}^{2} \}} - {\sum\limits_{u = 0}^{m}{E\{ {{y_{m}( {n,u} )}}^{2} \}}}}{E\{ {{z( {n,m} )}}^{2} \}} \rbrack^{\delta}$where 0<δ<1, E{|z(n,m)|²} is the power of input signal 108 in frequencyband m, and E{|y_(m)(n,u)|²} is the component echo power in frequencyband m due to the excitation caused by far end signal 102 in only bandu. As shown in the above formula for g(n,m), the component echo power infrequency band m due to the excitation caused by far end signal 102 ineach frequency band from 0 to m is subtracted from the power of inputsignal 108 in frequency band m.

Because the component echo power in frequency band m is not directlyknown, estimation must be done in terms of some quantity or variablewhich is known or measurable. Thus, in the present implementation, thecomponent echo power in frequency band m due to the excitation caused byfar end signal 102 in each band u may be estimated according to:E{|y _(m)(n,u)|² }=k _(m)(n,u)E{|x(n−D(m,u),u)|²}where k_(m)(n,u) is a weighting coefficient and E{|x(n−D(m,u),u)|²} isthe power of far end signal 102 in frequency band u, but delayed byD(m,u) timeframes. The delay is necessary because, as stated above, anynonlinear echo is a distorted, time-delayed version of far end signal102. The weighting coefficient is necessary because the power of theecho component in frequency band u is attenuated compared to theexciting far end signal 102 in frequency band u.

Delay D(m,u) is the echo delay of far end signal 102 in frequency band uwhich is exciting an echo in frequency band m. Thus, determining themagnitude of the delay may be estimated by determining the delay forwhich the normalized cross-correlation is maximized between the power ofinput signal 108 in frequency band m and the power of far end signal 102in frequency band u. For the purposes of the present application,cross-correlation may be considered to mean the mathematical correlationbetween two signals or functions where one of the signals is shiftedwith respect to the other. Thus, D(m,u) may be determined such that:

${{\frac{E\{ {z*( {n,m} ){x( {{n - d},u} )}} \}}{E\{ {{x( {{n - d},u} )}}^{2} \}}}\mspace{14mu}{is}\mspace{14mu}{maximized}\mspace{14mu}{at}\mspace{14mu} d} = {D( {m,u} )}$

Similarly, weighting coefficient k_(m)(n,u) may be estimated as thenormalized cross-correlation between the power of input signal 108 infrequency band m and the power of far end signal 102 in frequency bandm:

${k_{m}( {n,u} )} = {\frac{E\{ {z*( {n,m} ){x( {{n - {D( {m,u} )}},m} )}} \}}{E\{ {{x( {{n - {D( {m,u} )}},m} )}}^{2} \}}}$

The above technique, according to a first implementation, may be usedwhere a linear echo canceller is not employed. However, the abovetechnique may also be adapted to applications where a linear echocanceller is employed. In a second implementation, input signal 108,corresponding to z(n,m) may be replaced by residual signal 106,corresponding to e(n,m). Such a replacement may be made because, where alinear echo canceller is used, residual signal 106 may comprise theoriginal input signal 108 minus synthesized echo 105 cancelled by linearecho canceller 152, for example:e(n,m)=z(n,m)−{circumflex over (y)}(n,m)where e(n,m) corresponds to residual signal 106, z(n,m) corresponds toinput signal 108 and ŷ(n, m) corresponds to synthesized echo 105cancelled by linear echo canceller 152, for example. Thus, for thesecond implementation where a linear echo canceller is used:

${g( {n,m} )} = \lbrack \frac{{E\{ {{e( {n,m} )}}^{2} \}} - {\sum\limits_{u = 0}^{m}{E\{ {{y_{m}( {n,u} )}}^{2} \}}}}{E\{ {{e( {n,m} )}}^{2} \}} \rbrack^{\delta}$where 0<δ<1, E{|e(n,m)|²} is the power of residual signal 106 infrequency band m, and E{|y_(m)(n,u)|²} is the component echo power infrequency band m due to the excitation caused by far end signal 102 inonly band u. The component echo power in frequency band m due to theexcitation caused by far end signal 102 in each band u may be estimatedas in the first implementation:E{|y _(m)(n,u)|² }=k _(m)(n,u)E{|x(n−D(m,u),u)|²}

Echo delay D(m,u) of far end signal 102 in frequency band u, exciting anecho in frequency band m may be similarly estimated such that thenormalized cross-correlation is maximized between the power of residualsignal 106 in frequency band m and the power of delayed far end signal102 in frequency band u:

${{where}\mspace{14mu}{\frac{E\{ {e*( {n,m} ){x( {{n - d},u} )}} \}}{E\{ {{x( {{n - d},u} )}}^{2} \}}}\mspace{14mu}{is}\mspace{14mu}{maximized}\mspace{14mu}{at}\mspace{14mu} d} = {D( {m,u} )}$

Weighting coefficient k_(m)(n,u) may be estimated as the normalizedcross-correlation between the power of residual signal 106 in frequencyband m and the power of far end signal 102 in frequency band m:

${k_{m}( {n,u} )} = {\frac{E\{ {e*( {n,m} ){x( {{n - {D( {m,u} )}},m} )}} \}}{E\{ {{x( {{n - {D( {m,u} )}},m} )}}^{2} \}}}$

A third implementation teaches a second technique for nonlinear echosuppression, based on the synthesized echo estimated by a linear echocanceller. According to the third implementation, weighting coefficientg(n,m), for a frequency band m during timeframe n, may be computedprecisely as in the second implementation above:

${g( {n,m} )} = \lbrack \frac{{E\{ {{e( {n,m} )}}^{2} \}} - {\sum\limits_{u = 0}^{m}{E\{ {{y_{m}( {n,u} )}}^{2} \}}}}{E\{ {{e( {n,m} )}}^{2} \}} \rbrack^{\delta}$

As stated above, in the third implementation, the component echo powerin frequency band m due to the excitation caused by far end signal 102in each band u may be estimated based on synthesized echo 105 estimatedby linear echo canceller 152, for example, according to:E{|y _(m)(n,u)|² }=k _(m)(n,u)E{|ŷ(n,u)|²}where k_(m)(n,u) is the weighting coefficient and E{|ŷ(n,m)|²} is thepower of synthesized echo 105 in frequency band m, estimated by linearecho canceller 152, for example. In the third implementation no delay inŷ(n,m) is necessary because the estimation of synthesized echo 105 mayalready in clued adjustment for delay in the linear echo.

Weighting coefficient k_(m)(n,u) may be estimated as the normalizedcross-correlation between the power of residual signal 106 in frequencyband m and the power of synthesized echo 105 in frequency band u:

${k_{m}( {n,u} )} = {\frac{E\{ {e*( {n,m} ){\hat{y}( {n,u} )}} \}}{E\{ {{\hat{y}( {n,u} )}}^{2} \}}}$

The operation of system 100 of FIG. 1A will now be further discussedwith regard to FIGS. 2A-2F. FIGS. 2A-2F present exemplary diagrams ofseveral related signals present within a system for echo suppression,according to one implementation of the present application. For example,FIG. 2A may illustrate a far end signal, such as far end signal 102,comprising several components, each in one of M frequency bands. By wayof non-limiting illustration, M=4 in FIGS. 2A through 2F. However, thepresent application is not limited such a number of frequency bands andmay include implementations containing more or less than 4 frequencybands. Thus, components 210 a, 210 b, 210 c and 210 d may correspond tocomponents of far end signal 102, or x(n,u), in frequency bands f₀, f₁,f₂ and f_(M-1), respectively.

FIG. 2B demonstrates the echo components in each of the M frequencybands due to only the excitation caused by far end signal 102 infrequency band u=f₀, or 210 a. Thus, the excitation produced by far endsignal component 210 a may produce echo components 220 a, 220 b, 220 cand 220 d in frequency bands f₀, f₁, f₂ and f_(M-1), respectively.Similarly, FIG. 2C demonstrates the echo components in each of the Mfrequency bands due to only the excitation caused by far end signal 102in frequency band u=f₁, or 210 b. Thus, the excitation produced by farend signal component 210 b may produce echo components 230 a, 230 b, 230c and 230 d in frequency bands f₀, f₁, f₂ and f_(M-1), respectively.Likewise, FIG. 2D demonstrates the echo components in each of the Mfrequency bands due to only the excitation caused by far end signal 102in frequency band u=f₂, or 210 c. Thus, the excitation produced by farend signal component 210 c may produce echo components 240 a, 240 b, 240c and 240 d in frequency bands f₀, f₁, f₂ and f_(M-1), respectively.Finally, FIG. 2E demonstrates the echo components in each of the Mfrequency bands due to only the excitation caused by far end signal 102in frequency band u=f_(M-1), or 210 d. Thus, the excitation produced byfar end signal component 210 d may produce echo components 250 a, 250 b,250 c and 250 d in frequency bands f₀, f₁, f₂ and f_(M-1), respectively.

Thus, in accordance with one or more implementations of the presentapplication, the total echo in each frequency band m includes M echocomponents, one component due to the excitation caused by a far endsignal in each of the M frequency bands. FIG. 2F shows such a total echoin each frequency hand. For example, 260 a may represent the total echoin frequency band f₀ as the sum of each of the f₀ component echoes 220a, 230 a, 240 a and 250 a. Likewise, 260 b may represent the total echoin frequency band f₁ as the sum of each of the f₁ component echoes 220b, 230 b, 240 b and 250 b. 260 c may represent the total echo infrequency band f₂ as the sum of 220 a, 230 a, 240 a and 250 a, while 260d may represent the total echo in frequency band f_(M-1) as the sum ofeach of the f_(M-1) component echoes 220 d, 230 d, 240 d and 250 d.

The operation of system 100 of FIG. 1 will now be further described withrespect to FIGS. 3A through 3C. FIG. 3A presents an exemplary flowchartillustrating a method for echo suppression, according to oneimplementation of the present application. Action 310 of flowchart 300includes dividing an input signal into a plurality of frequency bands ineach of a plurality of timeframes. Such an action may be carried out byprocessor 124 of FIG. 1A, for example.

Continuing to action 320 of flowchart 300, action 320 includesmultiplying the input signal in each of the plurality of frequency bandsby a corresponding echo suppression signal. Because action 310 dividesan input signal into a plurality of frequency bands in each of aplurality of timeframes, an echo-suppressed signal may be obtained bydecreasing the amplitude or power of each frequency band of the inputsignal, containing a desired signal and the echo signal, by an amountthat correlates to the amplitude or power of the echo in that frequencyband. Such an action may be carried out by processor 124 of FIG. 1A forexample.

FIG. 3B presents an exemplary flowchart illustrating a method forestimating the corresponding echo suppression signal, according to oneimplementation of the present application. The actions disclosed in FIG.3B may be considered a subset of action 320 of FIG. 3A. Action 330 offlowchart 325 includes estimating a power of the echo signal in aparticular frequency band as a sum of a plurality of component echopowers. As disclosed above in FIGS. 2A through 2F echo in a particularfrequency band may be a sum of contributing echo components in thatparticular frequency band excited by far end signal 102 in each of the Mfrequency bands. However, because many loudspeakers only exhibit a fewstronger harmonics of a broadcast signal, computation costs may bereduced by utilizing only the stronger harmonics in estimating totalecho power. For example, echo in band m is most likely due toexcitations in bands u≦m/k where k is an integer. Accordingly, thepresent method may consider only the u=m, m/2 and m/3 echo components indetermining total echo for each frequency band m. How each of thecomponent echo powers may be estimated will be discussed in furtherdetail with respect to FIG. 3C.

Continuing with action 340 of flowchart 325, action 340 includessubtracting the power of the echo signal in the particular frequencyband from a power of the input signal in the particular frequency band.Such an action may be carried out by processor 124 of FIG. 1A, forexample.

Action 350 includes dividing by the power of the input signal in theparticular frequency band. Dividing by the power of the whole inputsignal acts to represent the resulting signal, which may represent theinput signal minus the echo, as a gain with which to multiply the inputsignal to achieve echo-suppressed signal 104, for example. Such anaction may be carried out by processor 124 of FIG. 1A, for example.

FIG. 3C presents an exemplary flowchart illustrating one or more methodsfor estimating each of the plurality of component echo powers. Theactions disclosed in FIG. 3C may be considered a subset of action 330 ofFIG. 3B. Action 360 of flowchart 375 includes applying a delay to thefar-end signal in the corresponding one of the plurality of frequencybands. As discussed above, each component echo in a particular frequencyband is excited by far end signal 102, for example, in each of the Mfrequency bands. Because echoes are inherently delayed from theirexciting signals, a delay must be applied to the far-end signal in orderto estimate each of the plurality of component echo powers. As discussedabove, the delay D(m,u) is chosen to maximize a cross-correlationbetween the input signal and the far end signal in the correspondingfrequency band. Such an action may be carried out by processor 124 ofFIG. 1A, for example.

Continuing with action 370 of flowchart 375, action 370 includesapplying a weight to the far-end signal in the corresponding one of theplurality of frequency bands. As discussed above, the weight k_(m)(n,u)may be a normalized cross-correlation between the input signal in theparticular frequency band and the far end signal in the particularfrequency band. Such an action may be carried out by processor 124 ofFIG. 1A, for example.

Action 380 of flowchart 375 may be utilized to estimate each of theplurality of component echo powers when a linear echo canceller isutilized, for example, linear echo canceller 152 as shown in FIG. 1B.Action 380 includes applying a weight to a synthesized echo in thecorresponding one of the plurality of frequency bands. Such asynthesized echo may represent an estimated linear echo as calculated bya linear echo canceller such as linear echo canceller 152 of FIG. 1B.Regarding action 380, the weight may be a normalized cross-correlationbetween the input signal in the m frequency band and the synthesizedecho in the corresponding frequency band of the component echo power, orthe u frequency band.

Thus, the present application provides for true nonlinear echosuppression. The concepts of the present application additionallyprovide for such echo suppression while markedly reducing associatedcomputation costs and increasing the speed of convergence of such echosuppression computations.

From the above description it is manifest that various techniques can beused for implementing the concepts described in the present applicationwithout departing from the scope of those concepts. Moreover, while theconcepts have been described with specific reference to certainimplementations, a person of ordinary skill in the art would recognizethat changes can be made in form and detail without departing from thespirit and the scope of those concepts. As such, the describedimplementations are to be considered in all respects as illustrative andnot restrictive. It should also be understood that the presentapplication is not limited to the particular implementations describedherein, but many rearrangements, modifications, and substitutions arepossible without departing from the scope of the present disclosure.

What is claimed is:
 1. A method for echo suppression, said methodcomprising: dividing an input signal into a plurality of frequency bandsin each of a plurality of time frames, said input signal comprising anecho signal; multiplying said input signal in each of said plurality offrequency bands by a corresponding echo suppression signal, whereincalculating said corresponding echo suppression signal comprises:estimating a power of said echo signal in a particular frequency band asa sum of a plurality of component echo powers, each of said plurality ofcomponent echo powers due to an excitation from a far-end signal in acorresponding one of said plurality of frequency bands; and subtractingsaid power of said echo signal in said particular frequency band from apower of said input signal in said particular frequency band; whereinestimating each of said plurality of component echo powers comprises:applying a delay to said far-end signal in said corresponding one ofsaid plurality of frequency bands; and applying a weight to said far-endsignal in said corresponding one of said plurality of frequency bands.2. The method of claim 1, wherein said calculating said correspondingecho suppression signal further comprises dividing by said power of saidinput signal in said particular frequency band.
 3. The method of claim1, wherein said echo signal is a residual echo signal from a linear echocanceller.
 4. The method of claim 1, wherein said plurality of componentecho powers are uncorrelated with one another.
 5. The method of claim 1,wherein said delay is chosen to maximize a cross-correlation betweensaid input signal and said far-end signal in said corresponding one ofsaid plurality of frequency bands.
 6. The method of claim 1, whereinsaid weight is a normalized cross-correlation between said input signalin said particular frequency band and said far-end signal in saidparticular frequency band.
 7. A method for echo suppression, said methodcomprising: dividing an input signal into a plurality of frequency bandsin each of a plurality of time frames, said input signal comprising anecho signal; multiplying said input signal in each of said plurality offrequency bands by a corresponding echo suppression signal, whereincalculating said corresponding echo suppression signal comprises:estimating a power of said echo signal in a particular frequency band asa sum of a plurality of component echo powers, each of said plurality ofcomponent echo powers due to an excitation from a far-end signal in acorresponding one of said plurality of frequency bands; and subtractingsaid power of said echo signal in said particular frequency band from apower of said input signal in said particular frequency band; whereinsaid echo signal is a residual echo signal from a linear echo canceller,and wherein estimating each of said plurality of component echo powerscomprises: applying a weight to a synthesized echo in said correspondingone of said plurality of frequency bands, said synthesized echo obtainedfrom a linear echo canceller.
 8. The method of claim 7, wherein saidweight is a normalized cross-correlation between said input signal insaid particular frequency band and said synthesized echo in saidcorresponding one of said plurality of frequency bands.
 9. The method ofclaim 1, wherein said plurality of component echo powers comprise onlycomponent echo powers due to an excitation from said far-end signal insaid corresponding one of said plurality of frequency bands, in afrequency band having a frequency of one half of said corresponding oneof said plurality of frequency bands, and in a frequency band having afrequency of one third of said corresponding one of said plurality offrequency bands.